Interference Cancellation Research Articles

Multiple and Reconfigurable Microwave Photonic Filter With Out-of-Band Interference Cancellation

Multiple and Reconfigurable Microwave Photonic Filter With Out-of-Band Interference Cancellation

An Accurate Non-contact Photoplethysmography via Active Cancellation of Reflective Interference.

Imaging Photoplethysmography (IPPG) is an emerging and efficient optical method for non-contact measurement of pulse waves using an image sensor. While the contactless way brings convenience, the inevitable distance between the sensor and the subject results in massive specular reflection interference on the skin surface, which leads to a low Signal to Interference plus Noise Ratio (SINR) of IPPG. To ease this challenge, this work proposes a novel modulation illumination approach to measure the accurate arterial pulse wave via surface reflection interference isolation from IPPG. Based on the proposed skin reflection model, a specific modulation illumination is designed to separate the surface reflections and obtain the subcutaneous diffuse reflections containing the pulse wave information. Compared with the results under ambient illumination and constant supplemental illumination, the SINR of the proposed method is improved by 4.56 and 3.74 dB, respectively.

An SIC-free NOMA-VLC system enhanced by multi-user rate allocation

Visible light communication (VLC) becomes a potential basic inter-connection technology for Internet of Things (IoT) services due to the advantages of ubiquitous light emitting diodes (LEDs). In this paper, a novel non-orthogonal multiple access (NOMA) scheme without serial interference cancellation (SIC) process is employed in baseband VLC system. The scheme is based on rate allocation and corresponding gain which could enhance the received signal to interference noise ratio (SINR). Simulation results show that the proposed scheme could achieve better bit error ratio and avoid error propagation (EP) compared to the conventional NOMA scheme.

A detailed reinforcement learning framework for resource allocation in non‐orthogonal multiple access enabled‐B5G/6G networks

AbstractThe world of communications technology has recently undergone an extremely significant revolution. This revolution is an immediate consequence of the immersion that the fifth generation B5G and 6G have just brought. The latter responds to the growing need for connectivity and it improves the speeds and qualities of the mobile connection. To improve the energy and spectral efficiency of these types of networks, the non‐orthogonal multiple access (NOMA) technique is seen as the key solution that can accommodate more users and dramatically improve spectrum efficiency. The basic idea of NOMA is to achieve multiple access in the power sector and decode the required signal via continuous interference cancelation. A resource allocation approach is proposed for the B5G/6G‐NOMA network that aims to maximise system throughput, spectrum and energy efficiency and fairness among users while minimising latency. The proposed approach is based on reinforcement learning (RL) with the use of the Q‐Learning algorithm. First, the process of resource allocation as a problem of maximising rewards is formulated. Next, the Q‐Learning algorithm is used to design a resource allocation algorithm based on RL. The results of the simulation confirm that the proposed scheme is feasible and efficient.

Hard Successive Interference Cancellation for M-QAM MIMO Links in the Presence of Rayleigh Deep-Fading.

In our paper, we propose a generalized version of the Alternating Projections Digital Hard Successive Interference Cancellation (AP-HSIC) algorithm that is capable of decoding any order of constellation M in an M-Quadrature Amplitude Modulation (QAM) system. Our approach applies to Rayleigh deep-fading Multiple-Input Multiple-Output (MIMO) channels with high-level Additive White Gaussian Noise (AWGN). It can handle various destructive phenomena without restricting the number of antenna arrays in the transmitter/receiver. Importantly, it does not rely on closed-loop MIMO feedback or the need for Channel-State Information Transmission (CSIT). We have demonstrated the effectiveness of our approach and provided a Bit Error Rate (BER) analysis for 16-, 32-, and 64-QAM modulation systems. Real-time simulations showcase the differences and advantages of our proposed algorithm compared to the Multi-Group Space-Time Coding (MGSTC) decoding algorithm and the Lagrange Multipliers Hard Successive Interference Cancellation (LM-HSIC) algorithm, which we have also developed here. Additionally, our paper includes a mathematical analysis of the LM-HSIC algorithm. The AP-HSIC algorithm is not only effective and fast in decoding, including interference cancellation computational feedback, but it can also be integrated with any Linear Processing Complex Orthogonal Design (LPCOD) technique, including Complex Orthogonal Design (COD) schemes such as high-order Orthogonal Space-Time Block Code (OSTBC) with high-order QAM symbols.

Iterative signal detection based soft interference cancellation for satellite-terrestrial downlink NOMA systems

Iterative signal detection based soft interference cancellation for satellite-terrestrial downlink NOMA systems

NOMA‐based precoded quadrature spatial modulation in multiuser MIMO downlink transmission over correlated channel

SummaryIn this paper, a non‐orthogonal multiple access (NOMA)‐based precoded quadrature spatial modulation (PQSM) technique (NOMA‐PQSM) has been proposed for the downlink scenario. In NOMA‐PQSM, two intended receiving antennas are activated at any time instant. One antenna is activated for the in‐phase component of the transmitted signal, and another one is activated for the quadrature phase component, on the basis of data bits. NOMA‐PQSM provides benefits like improved spatial diversity and spectral efficiency in comparison with spatial modulation. This work uses zero forcing (ZF) precoding over downlink flat fading Rayleigh multiple input multiple output (MIMO) channels, to limit the channel's deteriorating effect on transmitted signal, assuming perfect channel state information (CSI) at the transmitter. A low complexity receiver based on the successive interference cancellation is used. An expression for the upper bound of average bit error probability is derived. Moreover, the expressions for the sum mutual information of users and its lower bound are also derived. The proposed scheme is compared with the preprocessing aided spatial modulation (PSM)‐based counterpart. Monte Carlo simulations reveal that the NOMA‐PQSM scheme outperforms its orthogonal counterpart and the PSM scheme.

Real time implementation of downlink orthogonal frequency division multiplexing based non-orthogonal multiple access transceiver using NI USRP platform

The growing fame and utilization of wireless multimedia approaches have led to the advancement of the wireless system. The fifth generation (5G) of wireless communication was developed to serve users with enhanced proficiency, low latency, reliable communication, and lesser battery exhausts. The non-orthogonal multiple access (NOMA) scheme is a proficient multiple access scheme to fulfil the requirement of a 5G mobile system. NOMA enables a remarkable enhancement in the systems throughput and ability to connect devices. NOMA distinguishes each user by allocating a distinct power level, superimposing all the user’s signals utilizing superposition coding while transmitting and at the reception, each user’s signals are decoded by employing successive interference cancellation (SIC). This study builds a real time downlink orthogonal frequency division multiplexing based NOMA (OFDM-NOMA) transceiver system using the NI USRP 2944R and 2901 platforms. The performance evaluation of the proposed OFDM-NOMA system is carried out in terms of signal to noise ratio by adjusting transmitting gain and the distance of users from the base station system. Experimental results show that the signal-to-noise ratio (SNR) of each user relies on the power allocation factor and proximity of users from the base station, and SIC output is compared with constellation variations.

SemantIC: Semantic Interference Cancellation Toward 6G Wireless Communications

SemantIC: Semantic Interference Cancellation Toward 6G Wireless Communications

Mitigation of Suppressive Interference in AMPC SAR Based on Digital Beamforming

Multichannel Synthetic Aperture Radar (MC-SAR) systems, such as Azimuth Multi-Phase Centre (AMPC) SAR, provide an effective solution for achieving high-resolution wide-swath (HRWS) imaging by reducing the pulse repetition frequency (PRF) to increase the swath width. However, in an Electronic Countermeasures (ECM) environment, the image quality of multichannel SAR systems can be significantly degraded by electromagnetic interference. Previous research into interference and counter-interference techniques has predominantly focused on single-channel SAR systems, with relatively few studies addressing the specific challenges faced by MC-SAR systems. This paper uses the classical spatial filtering technique of adaptive digital beamforming (DBF). Considering the Doppler ambiguity present in the echoes, two schemes—Interference Reconstruction And Cancellation (IRC) and Channel Grouping Nulling (CGN)—are designed to effectively eliminate suppressive interference. The IRC method eliminates the effects of interference without losing spatial degrees of freedom, ensuring effective suppression of Doppler ambiguity in subsequent processing. This method shows significant advantages under conditions of strong Doppler ambiguity and low jammer-to-signal ratio. Conversely, the CGN method mitigates the effect of interference on multichannel imaging at the expense of degrees of freedom redundant to Doppler ambiguity suppression. It shows remarkable interference suppression performance under weak-Doppler-ambiguity conditions, allowing for better image recovery. Simulations performed on point and distributed targets have validated that the proposed methods can effectively remove interfering signals and achieve high-resolution wide-swath (HRWS) SAR images.

Pilot Assignment for Cell Free Massive MIMO Systems: A Successive Interference Cancellation Approach

In the contemporary era, considerable attention has been directed towards exploring cell-free massive multiple-input multiple-output (CF-M-MIMO) systems. This novel network paradigm has gained prominence as a potential solution for tackling the persistent challenge of inter-cell interference prevalent in traditional cellular MIMO networks. This study investigates a pilot assignment approach based on Successive Interference Cancellation (SIC) aimed at alleviating pilot contamination issues inherent in CF-M-MIMO systems. Through comprehensive numerical analyses and simulations, we demonstrate the efficacy and enhanced performance of the SIC-based approach competed with common random and greedy pilot assignment strategies. The proposed methodology addresses the critical challenge of pilot contamination, a phenomenon that severely impacts system performance and spectral efficiency. By iteratively decoding signals and canceling interference, the SIC algorithm optimizes pilot assignments, resulting in improved data rates and more efficient resource utilization. Our findings underscore the robustness and scalability of the SIC-based scheme across diverse system parameters and deployment scenarios, affirming its potential as a promising solution for enhancing the performance of CF-M-MIMO systems. Overall, this study contributes valuable insights into the design and optimization of pilot assignment strategies, offering a pathway for further research and development in the field of CF-M-MIMO systems.

Digital nonlinear self-interference cancellation using SW-GRU-TPA

In order to enhance spectrum utilization and decrease transmission delay, the 6th generation mobile networks (6G) system adopts full-duplex (FD) mode. Simultaneous operation of the same frequency inevitably causes the receiver to receive the signal sent by the transmitter, leading to serious nonlinear self-interference due to the nonlinear distortion generated by the power amplifier (PA). This paper proposes hybrid layer structures SW-GRU-TPA for the implementation of digital self-interference cancellation (SIC), combined with Sliding Window (SW), Gated Recurrent Unit (GRU), and Temporal Pattern Attention (TPA). The model can not only effectively utilize the influence of historical information on the signal, but also capture the spatial and temporal dependencies in the data to fit the nonlinear characteristics of the PA and the delay effect in multipath transmission. Meanwhile, by utilizing the L1 norm model pruning, the model parameters can be optimized, leading to improved processing efficiency. The model is verified using two methods: injection and antenna reception. Compared to the SW-GRU model with Attention Mechanism (AM), the Interference Cancellation Ratio (ICR) of injection and antenna increases by 3.13 dB and 2.01 dB, respectively. When the TPA is compressed by 42.17%, the ICR of injection and antenna decreases by 1.58% and 2.6%.

Multi-head self-attention mechanism combined with feedforward network for time-varying nonlinear digital self-interference cancellation

In-band full duplex (IBFD) allows simultaneous communication in the same frequency band, thus significantly improving spectral efficiency. However, self-interference (SI) at the local transmitter affects decoding at the receiver, and SI intensity increases when the channel is time-varying. Existing techniques concentrate on dealing with digital self-interference (DSI) in static channels, which are difficult to adapt to time-varying environments. For this purpose, firstly, the recursive least squares (RLS) method is utilized to counteract linear DSI. Secondly, a new feedforward neural network based on the multi-head self-attention mechanism (MHSAM-FFNN) is designed to eliminate dynamically changing nonlinear DSI. RLS can track signals and update linear coefficients. The self-attention mechanism computes the attention between any two signals in a time-varying sequence and aggregates the temporal relations by the obtained attention weights. MHSAM-FFNN utilizes multiple self-attention modules in parallel, which enhances the acquisition of different effective information in the time-varying sequence to better learn the feature relationships between the current signal and other signals. It ultimately reconstructing the nonlinearity and memory effects of DSI. As tested in different time-varying environments, results show that this paper's scheme successfully reduces DSI to the noise floor. In addition, this paper considers two scenarios where both the power amplifier (PA) and the low noise amplifier (LNA) are nonlinear and where PA is nonlinear while LNA is linear. Results demonstrate that our scheme can achieve higher interference cancellation in different nonlinear scenarios.

Optimization of resource allocation in 5G networks: A network slicing approach with hybrid NOMA for enhanced uRLLC and eMBB coexistence

SummaryTraditional Orthogonal Multiple Access (OMA) and spectrum sharing methods struggle to provide the diverse quality of service (QoS) demands for enhanced mobile broadband (eMBB), ultra‐reliable low latency communications (uRLLC), and massive machine type communications (mMTC) leading to suboptimal performance and service quality degradation. Single‐carrier‐non‐orthogonal multiple access (SC‐NOMA) appears to be a more optimized solution. It can serve multiple users simultaneously on the same time‐frequency resources. This approach offers both enhanced spectrum efficiency and meets the QoS requirements for the coexistence of eMBB, uRLLC, and mMTC. However, SC‐NOMA has some drawbacks. Decoding a user's signal involves a complex successive interference cancellation (SIC) process that gets harder with more users causing delays and errors. Additionally, strong user signals can interfere with weaker ones, limiting the number of users per channel. In order to overcome the drawbacks associated with OMA and SC‐NOMA, this paper introduces a new method called user‐paired NOMA (hybrid NOMA). Hybrid NOMA adopts a strategic approach, employing two user pairing techniques: near‐far/far‐near (NF‐FN) and near‐near/far‐far (NN‐FF). NF‐FN pairing prioritizes users with similar signal strengths but different distances from the base station. This minimizes interference for the weaker user during SIC. NN‐FF pairing, on the other hand, groups users with similar signal strengths and proximity. This approach further simplifies SIC and minimizes potential interference altogether. The simulation results demonstrate trade‐offs between eMBB and uRLLC performance. OMA suffers with dedicated resource allocation, while SC‐NOMA balances performance but experiences interference. NN‐FF prioritizes eMBB and offers best latency, while NF‐FN prioritizes uRLLC with high spectral efficiency but suffers from higher latency. Finally, by providing a thorough grasp of how hybrid NOMA resource allocation works to improve the performance of various use cases, this research makes a significant contribution to the field of 5G spectrum optimization.

A framework for co-existence of radar and communication with joint design

The integration of both sensing and communication functions is a crucial feature for future communication systems. This paper considers a novel scenario where a radar covers multiple small-cell base stations which operate in different spectra. Due to the limited spectra resource, the radar needs to reuse the spectra of one BS for tracking. To suppress interference and improve performance, we propose a framework including two stages and the corresponding communication and sensing algorithms. Specifically, at the detection stage, we aim to minimize the system transmit power while maintaining the performance of both radar and communication. At the tracking stage, our goal is to maximize the radar sensing performance under a given power budget, while ensuring communication quality. Due to the complexity of the original problem, we address it by introducing auxiliary variables and proposing a penalty dual decomposition-based algorithm, enabling us to solve a more tractable form of the problem. In the inner loop, we propose a concave–convex procedure-based algorithm to handle the optimization problem, while adopting the block coordinate descent algorithm to iteratively update the variables. In the outer loop, we update the penalty term or Lagrange multipliers. Furthermore, we propose a radar target parameter estimation algorithm based on successive interference cancellation, which aims to mitigate communication interference. Finally, numerical simulations demonstrate the effectiveness of the proposed system, and the superior performance of our proposed algorithms over benchmark algorithms.

Effective capacity of STAR-RIS assisted RSMA network with imperfect SIC

The proliferation of various Internet of Everything applications places urgent demand for high energy efficiency, massive connection and wide coverage for the future communication era. Motivated by this, rate-splitting multiple access (RSMA) and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has attracted wide publicity from industry and academia. In this paper, we consider a STAR-RIS assisted two-user RSMA network with imperfect successive interference cancellation, and all channels are modeled as Nakagami-m distribution. By adopting effective capacity (EC) as the metric, we analyze the system performance under certain quality-of-service constraint. Specifically, analytical expressions of EC for a pair of RSMA users are provided. To explore further insights, high signal-to-noise ratio (SNR) conditions are also considered. Furthermore, the effect of some specific elements on system EC performance are analyzed, and some significant conclusions are obtained as follows: (1) As SNR grows, the effective capacities of two users improve, but finally converge to constant at high SNR. (2) The increase in the amount of the STAR-RIS elements can obviously increase the effective capacities. (3) Compared to traditional STAR-RIS assisted non-orthogonal multiple access networks, STAR-RIS assisted RSMA network has distinct advantages to improve system EC performance.

Progressive Inter-Path Interference Cancellation Algorithm for Channel Estimation Using Orthogonal Time-Frequency Space.

Fractional delay-Doppler (DD) channel estimation in orthogonal time-frequency space (OTFS) systems poses a significant challenge considering the severe effects of inter-path interference (IPI). To this end, several algorithms have been extensively explored in the literature for accurate low-complexity channel estimation in both integer and fractional DD scenarios. In this work, we develop a variant of the state-of-the-art delay-Doppler inter-path interference cancellation (DDIPIC) algorithm that progressively cancels the IPI as estimates are obtained. The key advantage of the proposed approach is that it requires only a final refinement procedure reducing the complexity of the algorithm. Specifically, the time difference in latency between the proposed approach and the DDIPIC algorithm is almost proportional to the square of the number of estimated paths. Numerical results show that the proposed algorithm outperforms the other channel estimation schemes achieving lower normalized mean square error (NMSE) and bit error rate (BER).

Joint Optimization of Age of Information and Energy Consumption in NR-V2X System Based on Deep Reinforcement Learning.

As autonomous driving may be the most important application scenario of the next generation, the development of wireless access technologies enabling reliable and low-latency vehicle communication becomes crucial. To address this, 3GPP has developed Vehicle-to-Everything (V2X) specifications based on 5G New Radio (NR) technology, where Mode 2 Side-Link (SL) communication resembles Mode 4 in LTE-V2X, allowing direct communication between vehicles. This supplements SL communication in LTE-V2X and represents the latest advancements in cellular V2X (C-V2X) with the improved performance of NR-V2X. However, in NR-V2X Mode 2, resource collisions still occur and thus degrade the age of information (AOI). Therefore, an interference cancellation method is employed to mitigate this impact by combining NR-V2X with Non-Orthogonal multiple access (NOMA) technology. In NR-V2X, when vehicles select smaller resource reservation intervals (RRIs), higher-frequency transmissions use more energy to reduce AoI. Hence, it is important to jointly considerAoI and communication energy consumption based on NR-V2X communication. Then, we formulate such an optimization problem and employ the Deep Reinforcement Learning (DRL) algorithm to compute the optimal transmission RRI and transmission power for each transmitting vehicle to reduce the energy consumption of each transmitting vehicle and the AoI of each receiving vehicle. Extensive simulations demonstrate the performance of our proposed algorithm.

Outage and throughput performance analysis of incremental relaying‐based underlay cognitive nonorthogonal multiple access networks with maximal ratio combining

SummaryIn this paper, we investigate the effectiveness of incremental relaying (IR)‐based underlay cognitive nonorthogonal multiple access (CNOMA) system with maximal ratio combining (MRC). Considering imperfect successive interference cancelation (i‐SIC), we derive analytical expressions for the outage probabilities experienced by the secondary users (SUs) and the system outage probability of the IR‐CNOMA system. We also derive the analytical expression for the outage probability of far SUs by considering IR‐CNOMA system with MRC. The maximum transmit power constraint of the secondary nodes and the interference threshold constraint of the primary receiver are considered in the analysis. We also evaluate the system throughput of IR‐CNOMA network. We also derive outage and throughput expression for the traditional cooperative relaying‐based CNOMA system (CR‐CNOMA) for the purpose of comparison. We derive analytical expression for the asymptotic outage probability and the asymptotic system outage probabilities of the SUs of IR‐CNOMA system. Further, we derive expressions for the optimal power allocation (OPA) factor at the secondary source that minimizes the asymptotic system outage probability of the IR‐CNOMA system. Through numerical and simulation investigations, we demonstrate that the system outage probability significantly lowers when the OPA factor is selected based on the criteria outlined in this work. It can be observed from the results that the IR‐CNOMA system outperforms the conventional CR‐CNOMA system in terms of outage probabilities and throughput. The outage probability is further reduced when IR‐CNOMA system with MRC is considered for the far SUs.

Performance of Smart Grid Based on Data Aggregation Using Wireless Communication Network Technology

With the advancements in technology, electrical energy has become a basic need to support every field of life including Electric Vehicles (EVs), Industry automation, security networks and communication systems. This, in turn, demands a high order of design, protection and measurement setup of power transmission from the energy source to the end users (load) with minimum loss of energy. All types of loads need a nominal supply voltage to operate, which necessary for its safe operation. Usually the nominal-rated voltage allows ±5% variation tolerance in the operation of loads, without affecting the equipment. The transmission lines that connect several smart grids are called as interconnection, by using it the stability and proficiency can be increased. It should provide reliable and secure communication, with a low-cost solution. Hence, in this research paper, an efficient communication system based on wireless sensor networks will be under consideration, to ensure good quality of service for smart grids. The initial two points that are required to be covered include 1) research on optimum network topology to connect several smart grids and 2) interference cancellation to avoid errors in transmission due to the induced field from the power lines. In addition, 3) the wireless sensor network will be used to support efficient data collection, self-organization of the network and data reduction by removing the redundancy. Finally, 4) development of data prediction algorithm to reduce the transmission rate and latency. Overall, these approaches will help in development of smart network to reduce the energy wastage, ensure nominal supply voltage, increased reliability and improved communication network as compared to existing solutions. The presented work includes the two sorts of wind and solar energy in ordinary working environments and illuminates the energy trade between buyers and power Production Company. The expense of power isn't thought about; however, the various buyers can pick the least expensive energy.